MiDAS - Meaningful Immunogenetic Data at Scale

Migdał, Maciej; Ruan, Dan Fu; Forrest, William F.; Horowitz, Amir; Hammer, Christian

doi:10.1101/2021.01.12.425276

Cited by 4 publications

(1 citation statement)

References 32 publications

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“…For the evaluation of HLA typing presented in this paper, we used all known HLA alleles from the IPD-IMGT/HLA sequence database v3.32, excluding unconfirmed alleles and those with a population allele frequency < 0.05 according to the Allele Frequency Net Database [16,17] as input haplotype sequences and GRCh38 version 106 from Ensembl as reference genome. For now, we did not group individual variants into MNVs or complex replacements (but aim to pursue this in future work, see section 5).…”

Section: Generation Of Candidate Haplotypes and Variantsmentioning

confidence: 99%

Orthanq: transparent and uncertainty-aware haplotype quantification with application in HLA-typing

Uzuner,

Köster,

Schadendorf

et al. 2024

Preprint

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Background Identification of Human leukocyte antigen (HLA) types from DNA-sequenced human samples is important in organ transplantation and cancer immunotherapy and remains a challenging task considering sequence homology and extreme polymorphism of HLA genes. Results We present Orthanq, a novel statistical model and corresponding application for transparent and uncertainty-aware quantification of haplotypes. We utilize our approach to perform HLA typing while, for the first time, reporting uncertainty of predictions and transparently observing mutations beyond reported HLA types. Using 99 gold standard samples from 1000 Genomes, Illumina Platinum Genomes and Genome In a Bottle projects, we show that Orthanq can provide superior accuracy and shorter runtimes than state-of-the-art HLA typers. Conclusions Orthanq is is the first approach that allows to directly utilize existing pangenome alignments and type all HLA loci. Moreover, it can be generalized for usages beyond HLA typing, e.g. for virus lineage quantification. Orthanq is available under https://orthanq.github.io.

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Section: Generation Of Candidate Haplotypes and Variantsmentioning

confidence: 99%

Orthanq: transparent and uncertainty-aware haplotype quantification with application in HLA-typing

Uzuner,

Köster,

Schadendorf

et al. 2024

Preprint

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PGNneo: A Proteogenomics-Based Neoantigen Prediction Pipeline in Noncoding Regions

Tan

Xu²,

Jian³

et al. 2023

Cells

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The development of a neoantigen-based personalized vaccine has promise in the hunt for cancer immunotherapy. The challenge in neoantigen vaccine design is the need to rapidly and accurately identify, in patients, those neoantigens with vaccine potential. Evidence shows that neoantigens can be derived from noncoding sequences, but there are few specific tools for identifying neoantigens in noncoding regions. In this work, we describe a proteogenomics-based pipeline, namely PGNneo, for use in discovering neoantigens derived from the noncoding region of the human genome with reliability. In PGNneo, four modules are included: (1) noncoding somatic variant calling and HLA typing; (2) peptide extraction and customized database construction; (3) variant peptide identification; (4) neoantigen prediction and selection. We have demonstrated the effectiveness of PGNneo and applied and validated our methodology in two real-world hepatocellular carcinoma (HCC) cohorts. TP53, WWP1, ATM, KMT2C, and NFE2L2, which are frequently mutating genes associated with HCC, were identified in two cohorts and corresponded to 107 neoantigens from non-coding regions. In addition, we applied PGNneo to a colorectal cancer (CRC) cohort, demonstrating that the tool can be extended and verified in other tumor types. In summary, PGNneo can specifically detect neoantigens generated by noncoding regions in tumors, providing additional immune targets for cancer types with a low tumor mutational burden (TMB) in coding regions. PGNneo, together with our previous tool, can identify coding and noncoding region-derived neoantigens and, thus, will contribute to a complete understanding of the tumor immune target landscape. PGNneo source code and documentation are available at Github. To facilitate the installation and use of PGNneo, we provide a Docker container and a GUI.

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Molecular Analysis of HLA Genes in Romanian Patients with Chronic Hepatitis B Virus Infection

Tălăngescu,

Calenic,

Mihăilescu

et al. 2024

CIMB

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Hepatitis B, a persistent inflammatory liver condition, stands as a significant global health issue. In Romania, the prevalence of chronic hepatitis B virus (CHB) infection ranks among the highest in the European Union. The HLA genotype significantly impacts hepatitis B virus infection progression, indicating that certain HLA variants can affect the infection’s outcome. The primary goal of the present work is to identify HLA alleles and specific amino acid residues linked to hepatitis B within the Romanian population. The study enrolled 247 patients with chronic hepatitis B; HLA typing was performed using next-generation sequencing. This study’s main findings include the identification of certain HLA alleles, such as DQB1*06:03:01, DRB1*13:01:01, DQB1*06:02:01, DQA1*01:03:01, DRB5*01:01:01, and DRB1*15:01:01, which exhibit a significant protective effect against HBV. Additionally, the amino acid residue alanine at DQB1_38 is associated with a protective role, while valine presence may signal an increased risk of hepatitis B. The present findings are important in addressing the urgent need for improved methods of diagnosing and managing CHB, particularly when considering the disease’s presence in diverse population groups and geographical regions.

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MiDAS - Meaningful Immunogenetic Data at Scale

Cited by 4 publications

References 32 publications

Orthanq: transparent and uncertainty-aware haplotype quantification with application in HLA-typing

Orthanq: transparent and uncertainty-aware haplotype quantification with application in HLA-typing

PGNneo: A Proteogenomics-Based Neoantigen Prediction Pipeline in Noncoding Regions

Molecular Analysis of HLA Genes in Romanian Patients with Chronic Hepatitis B Virus Infection

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